Ideas and Strategies for Real-Time Personalization

With the end of 2015 fast approaching, one thing is clear: our data is giving us cabin fever. From CPG to travel, retail, and financial services, companies are collecting volumes of audience data. We’re storing what blog articles they’re reading, which emails they’re opening, and what product pages they’re browsing. But much of that information is going unused.

The reason? Passive data collection is tough to wrangle. In monitoring everything, we’re having a tough time narrowing down our options and focusing on the business stories that matter post. We’re looking for trends before we’ve established the questions that we want answered. And one of the toughest questions for consumer-facing businesses to answer is how to deliver effective product recommendations.

Given the wealth of data that your company is collecting, how do you make sure that you’re making the right judgment calls? Do your audiences care about the products you’re showing them? Are your recommendations effective?

1. Interview your customers, host a focus group, or run online user tests Find out how they’re browsing your website, and how they make their purchase decisions. Ask some of the following questions:

What types of products are you shopping for now?

What types of product photos appeal to you?

What makes you want to click on a recommended product?

How do you naturally source product recommendations?

Which retailers provide the best product recommendations, and why?

Which retailers provide the worst product recommendations, and why?

The goal isn’t to collect survey data or detect quantitative trends. Instead it’s to detect patterns and areas of inspiration. Your customers tell a business story that’s completely different from the one that you see as a marketer every day. Use customer conversations to inspire your next analysis.

2. Come up with customer stories When it comes to effective product recommendations, context is everything. It’s important to understand what shoppers are doing and, more importantly, why, when putting together your approach.

Use your customer conversations from step 1 to understand the process that your audience is following to make buying decisions. Also pay attention to their pain points. With this empathy, you’ll be able to design more effective recommendation strategies. Much like product development, when you focus on the problem rather than the solution, you build a more effective resource.

3. Read up on your psychology Human psychology is a powerful marketing force – especially when it comes to digital marketing. If your job is to build relationships with audiences online, you’ll benefit from understanding patterns in shopping behavior. For one, recent studies say that consumer trust in marketing is low. Others reports say that people are most influenced by product recommendations from friends and family.

These psychology studies can help you come up with variables to include in your algorithms and angles from which to analyze your data. Uncover some general trends around why people make the decision to buy. Test out some concepts (i.e. a social feature) with your product recommendations.

Final Thoughts These 3 steps will help you find more meaning in your data--and better prepare you take action upon it. Success with data isn’t about the numbers. It’s about the context and performance benchmarks that you’re establishing and measuring against. Know what your customers care about, what business questions you care about, and what goals you want to achieve.